code: def testRunsWithLstmStack(self, lstm_size, rnn_construction_fn):
      observation_spec = tensor_spec.BoundedTensorSpec(
          (8, 8, 3), tf.float32, 0, 1
      )
      time_step_spec = ts.time_step_spec(observation_spec)
      time_step = tensor_spec.sample_spec_nest(
          time_step_spec, outer_dims=(1, 5)
      )
  
      action_spec = [
          tensor_spec.BoundedTensorSpec((2,), tf.float32, 2, 3),
          tensor_spec.BoundedTensorSpec((3,), tf.int32, 0, 3),
      ]
  
      net = actor_distribution_rnn_network.ActorDistributionRnnNetwork(
          observation_spec,
          action_spec,
          conv_layer_params=[(4, 2, 2)],
          input_fc_layer_params=(5,),
          output_fc_layer_params=(5,),
          lstm_size=lstm_size,
          rnn_construction_fn=rnn_construction_fn,
          rnn_construction_kwargs={"lstm_size": 3},
      )
  
      initial_state = actor_policy.ActorPolicy(
          time_step_spec, action_spec, net
      ).get_initial_state(1)
      net_call = net(
          time_step.observation, time_step.step_type, initial_state
      )
  
      self.evaluate(tf.compat.v1.global_variables_initializer())
      self.evaluate(
          tf.nest.map_structure(lambda d: d.sample(), net_call[0])
      )
  
file_path: agents/tf_agents/networks/actor_distribution_rnn_network_test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import tensorflow
  from tf_agents.networks import actor_distribution_rnn_network
  from tf_agents.policies import actor_policy
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import time_step
label_desc: Use image node_id 3 for calling the ActorDistributionNetworkTest obj's underlying member method code with example usage: obj.testRunsWithLstmStack(lstm_size, rnn_construction_fn) without return types